Staff Software Engineer, Credit Insights — Scale ML Lending

Plaid; New York (NY); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Equity

Commission opportunity

Medical insurance

401(k)

Dental & Vision

Job summary

Plaid is building the future of credit decisioning with a platform that enables lenders to make holistic, data-driven decisions at scale. The team will define architecture for credit insights and work with data science and ML partners to productionize new capabilities.

The role emphasizes mentoring, cross-functional collaboration, and delivering production-grade systems that support ML models, with potential exposure to credit/lending domains.

Qualifications

• Strong experience building and scaling backend products.
• Strong technical leadership skills, including mentoring peers, leading projects and driving architectural decisions.
• Demonstrated success in building and maintaining production systems that serve and support ML models, both in online and offline settings - as well as working closely with data science or ML teams.
• Experience collaborating with cross-functional stakeholders and with teams and leaders across the engineering function.
• Nice-to-have: experience working in the credit or lending space.

Responsibilities

• Leading technical architecture and execution across credit insights products: data fetching, online feature serving, offline production pipelines, and model training tooling.
• Scaling architecture to support ~100x load increases.
• Collaborating with Product, Data Science, and ML teams to develop and scale insights for Credit underwriting.
• Mentoring engineers and contributing to a strong, inclusive team culture.

Skills

Backend architecture

Technical leadership

Production systems

Cross-functional collaboration

ML model integration

Tools

AWS

Spark

Job description

Plaid is building the future of credit decisioning with a platform that enables lenders to make holistic, data-driven decisions at scale. The team will define architecture for credit insights and work with data science and ML partners to productionize new capabilities.

The role emphasizes mentoring, cross-functional collaboration, and delivering production-grade systems that support ML models, with potential exposure to credit/lending domains.